Estimate Survival Function for the Breast Cancer Disease by using GRD
Estimate Survival Function for the breast cancer disease by using Generalized Raleigh distribution
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This book deals with estimating the shape and scale parameters together in generalized Rayleigh distribution by using three Nonbayesian (classical) and three Bayesian methods (MLE, OLSE, RSSE, SBE, LAE and SE), then using these methods to estimate related probability functions; death density function, cumulative distribution function, survival function and hazard function (rate function). Using a sample of real data taken from Educational Hospital in Diwaniya and collect data which describe the duration of survivor for the patients who suffers from breast cancer based on diagnosis of disease o...
This book deals with estimating the shape and scale parameters together in generalized Rayleigh distribution by using three Nonbayesian (classical) and three Bayesian methods (MLE, OLSE, RSSE, SBE, LAE and SE), then using these methods to estimate related probability functions; death density function, cumulative distribution function, survival function and hazard function (rate function). Using a sample of real data taken from Educational Hospital in Diwaniya and collect data which describe the duration of survivor for the patients who suffers from breast cancer based on diagnosis of disease or the patient's admission to a hospital. The two-parameters in generalized Rayleigh distribution were computed and estimated by using the five previously mentioned methods, then the death, survival and hazard functions were computed and estimated and finally the Wald test was applied for all parameters in generalized Rayleigh distribution for all Nonbayesian and Bayesian methods.
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